Huawei R&D Sites in Belgium and the Netherlands Jobs

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2022年荷比卢研发类实习生招聘

Amsterdam & Leuven, Belgium

Student

Huawei Leuven Research Center

招聘岗位名称

岗位职责

岗位要求

射频芯片设计实习生

负责全频谱泛ICT射频芯片系统设计以及射频芯片电路开发（TRX、PA、LNA、Mixer、PLL/VCO、VGA、TIA、Driver、CDR、AD/DA等主要模块）、射频芯片验证、射频芯片工艺、建模、可靠性等相关工作。

1、微电子与固体电子学、电子科学与技术、电路与系统、通信工程、电磁场等相关专业，本科及以上学历；

2、善于团队合作，中英文语言流利。

模拟芯片设计实习生

负责数模混合芯片中模拟电路的详细设计、实现、验证等工作，包括Serdes、数模/模数转换器、PLL、PMU、PHY、IoT、CMOS高频电路及频域转换电路等。

1、微电子与固体电子学、电子科学与技术、电路与系统、通信工程、电磁场等相关专业，本科及以上学历；

2、善于团队合作，中英文语言流利。

数字芯片设计实习生

1、负责数字芯片的详细设计、实现和维护以及综合、形式验证、STA、CRG设计等工作；

2、及时编写各种设计文档和标准化资料，理解并认同公司的开发流程、规范和制度，实现资源、经验共享。

1、微电子、计算机、通信工程、自动化、电磁场等相关专业；

2、善于团队合作，中英文语言流利。

网络基础理论实习生

1、参与总部网络优化方向关键技术的研究与创新突破；

2、关键技术研究成果仿真验证。

1、数学专业或理工类学科有意愿从事理论研究的；

2、善于团队合作，中英文语言流利；

3、有数学相关竞赛背景优先。

芯片安全实习生

1、参与芯片安全的洞察工作，整理洞察报告；

2、参与部分项目的方案分析及方案设计和验证。

1、电子、半导体、芯片安全，计算机体系结构，密码学等相关专业，具备系统架构设计，密码学等基础知识；

2、善于团队合作，中英文语言流利。

低功耗实习生

1、低功耗相关技术分析及分析报告；

2、多核多系统计算低功耗技术分析及参与相关方案或设计工作；

3.、低功耗实现低功耗分析及参与相关方案设计工作。

1、数学，统计系（或者数学系里的统计系），数模结合，电子、半导体，芯片设计等相关专业；

2、善于团队合作，中英文语言流利。

SOC系统架构实习生

1、SOC 性能，低功耗等方向技术分析及分析报告；

2、参与相关项目及方案，设计工作。

1、电子、半导体、计算架构，SOC设计，芯片量产及可靠性等相关专业，具备系统架构设计，芯片实现基础知识尤佳；

2、善于团队合作，中英文语言流利。

芯片多媒体实习生

1、参与音频/视频相关的洞察工作，整理洞察报告；

2、参与部分项目的方案分析及方案设计和验证。

1、电子、半导体、声学、信号与系统，阵列信号处理，微电子等相关专业，有CODEC，smartpa，dmic相关背景尤佳；

2、善于团队合作，中英文语言流利。

自然语言处理/语音语义实习生

1、从事语音识别与合成、机器翻译、对话和问答系统、深度自然语言处理、多模态语义理解、知识图谱等方向的应用研究和开发工作；

2、负责自然语言处理核心算法及平台的设计与研发，提升华为终端手机等相关产品的核心竞争力和用户体验。

1、计算机科学、机器学习、统计学、应用数学等相关专业；

2、善于团队合作，中英文语言流利。

机器学习/计算机视觉实习生

1、从事机器学习算法和理论前沿研究，研究领域包括：元学习，AutoML, 深度学习，强化学习，贝叶斯学习等；

2、探索人工智能应用，构建智能系统，提供AI云服务；

3、从事计算机视觉、模式识别、多媒体内容分析等方向的应用研究和开发工作；如3D重建、图像超分、OCR、多目标跟踪、场景识别等；

4、负责计算视觉核心算法及平台的设计与研发，提升公司相关产品的核心竞争力和用户体验；应用场景包括视频监控、智能摄影、车辆视觉等。

1、计算机科学、机器学习、统计学、应用数学等相关专业；

2、善于团队合作，中英文语言流利。

推荐搜索/决策推理实习生

1、洞察推荐系统和信息检索技术在工业级产品的有效解决方案；洞察学术界推荐系统和信息检索的最新研究成果；

2、以下方向的决策推理：

方向一：下一代CT/IT智能运维体系

方向二：下一代CT/数据中心/云计算智能管理&控制体系

方向三：自动驾驶

方向四：企业智能

1、计算机科学、机器学习、统计学、应用数学等相关专业；

2、善于团队合作，中英文语言流利。

AI软件/应用软件实习生

1、在这里，你可以接触最前沿的软件领域技术，参与开发业界最优秀的手机、平板、可穿戴、智能家居、车载等全品类终端精品；

2、在这里，你可以创作极致用户体验的应用APP，围绕鸿蒙生态从事HarmonyOS应用软件研发，以最快的速度看到你贡献的代码被成千上万人使用；

3、在这里，你可以接触到业内先进的开发模式与开发工具，与前辈们进行平等的沟通交流，快速成长。

1、计算机、通信、软件工程等相关专业本科及以上学历；

2、对终端产品软件开发充满激情；

3、善于团队合作，中英文语言流利。

大数据开发实习生

1、深度参与到华为大数据Hadoop、Yarn、Spark、Hive、HBase、Kafka、Zookeeper、Flume、AI平台等组件的研发、交付及解决方案支撑； 2、探索云服务化实现的前沿技术，并负责华为云大数据服务的架构设计、开发、测试及运维。

1、计算机、软件相关专业本科及以上学历；

2、善于团队合作，中英文语言流利。

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3GPP SA2 Standardization Expert

Leuven, Belgium

Employee

Remote during pandemic

Huawei Leuven Research Center

The role requires familiarity with wireless communication technologies and standard developed by 3GPP, and experience in wireless communication research and attending 3GPP standardization meeting as a delegate.

We are looking for a 3GPP SA2 Standardization Expert/Delegate, who will be responsible to be a delegate to attend 3GPP SA2 WG meetings. His/her primary focus will be the improvement of the Huawei Terminal’s leadership in the 3GPP by involving in the technical discussions and the communicating with other major companies.

The successful candidate will work alongside researchers, domestic standard delegates, engineers and developers, who contribute on different aspects of the project. Therefore, commitment to collaborative problem-solving, advanced design methods and the creation of quality products are essential attributes.

The company is putting together a new, dynamic, geographically-distributed team. The successful candidate will be given a choice of working either in Leuven (Belgium) or Cambridge (UK).

Responsibilities:

Participate in the 3GPP SA2 meeting, lead and promote the initiation of SA2 subject standards, including obtaining the position of project rapporteur, and improve the voice and influence of Huawei Device on standards.
Fully understand the standard requirements of the product line, develop the standard promotion strategy and plan, and promote the strategy and plan at the SA2 standard meeting.
Gain insights into the research direction of innovative technologies oriented to device business applications, and provide important input and suggestions for team innovation research.
Promote SEP in SA2 work items.
Provide guidance for team members and help them improve their capabilities in the SA2 business domain

Travelling: International travel.

Qualifications and Skills:

Knowledge of wireless communication technologies and standard developed by 3GPP.
Experience and expertise as a 3GPP delegate.
Ability to understand business requirements and translate these into technical requirements.
Well communication skills, especially intercultural communication.

Languages: fluent English (spoken and written).

Desirable soft skills: adaptability (including culture-sensitive outlook), written and verbal communication, time management, stress management, conflict management.

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Academic Cooperation Manager

Amsterdam-Zuidoost, Netherlands

Freelance

Huawei Amsterdam Research Center

We are looking for an expert (m/f) who has significant experience in the field of cooperation management in the industry.

If you are enthusiastic to shape the future of Huawei Amsterdam Research Center together with us, find it attractive to work on a very high level of technical innovation and being part of a multicultural team and growing environment, please contact us.

Job Responsibilities

Based on the company's business development and long-term competitiveness building requirements, keep exploring valuable academic collaboration research ideas, responsible for the research topic exploring, proposals analysis, requirement analysis, topic application and defense, project execution. Covering AI research fields such as NLP, CV, IR, and KG.
Responsible for tracking and watching opportunities in EU and Netherlands national projects, developing proposals, consortium setting up, and coordinating project implementation as coordinator;
Continuously analyse TOP academic resources of top Netherlands universities, recommending and reporting relevant academic resources and cooperation opportunities based on the company's business development needs.
Maintain and enhance cooperation relationship with Netherlands universities, organizing various academic activities, including academic seminars, technical summits, academic reports, etc.

Position requirements:

Engineering education background, computer science, information science, applied mathematics or related science disciplines, PhD degree is preferred;
Have at least three years of research background or project experience in AI fields such as NLP, CV, IR, and KG.
Experiences in EU projects such as Horizon Europe or Netherlands national projects is preferred.
Fluency in English, strong communication skills, writing and presentation skills;
Chinese native speaker , Dutch native speaker are preferred.
Familiar with Dutch universities channels. Management relationships and contacts are preferred.

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Data Annotation Specialist

Amsterdam-Zuidoost, Netherlands

Freelance

Huawei Amsterdam Research Center

For our R&D Centre in Amsterdam we are looking for a Data Annotation Specialist to join our team

About The Job

You'll work as an integral part of an operational team, sifting language materials against requirements to identify reportable intelligence that will be forwarded to analysts to help shape and influence their operational decision making.

As a Data Annotation Specialist, you will be involved into evaluating the performance of the system, annotating linguistic data and working closely with our engineering teams.

You will use your analytical mindset, strong communication skills, collaborative attitude, and personal drive to increase the performance of the system

Tasks:

Evaluate the system performance from consumer’s perspective, and annotate linguistic data to optimize web search experience
Provide accurate annotations for Machine Translation and Speech to Text content, as well as other language related AI models.
Test the platform system, collect all bugs and flaws, categorize them into charts, and prepare detailed reports for the tech team to solve the issues

Qualifications

1+ years of experience in Analytical, Logical, Eye for detail and self-learning with minimal support
Tech Savvy, comfortable using internet based applications - surveys
Native local language level & deep appreciation of local nuances (Arabic, German, Turkish, French, Spanish or Russian)
Bilingual skills is a plus
Have in-depth, up-to-date familiarity with current country's social culture, media, and web culture Good web research skills and analytical abilities.
Good web research skills and analytical abilities.
Proficient communication skills in English is a must.
Being stress resilient and flexible

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Director of R&D Silicon Photonics

Gent, Belgium

Employee

Partial Remote Job

Huawei Gent Research Center

Huawei Technologies R&D Belgium is a centre of excellence for silicon photonics design and processing. It was initially created as a spin-off from the University of Gent and Imec in 2010 and then acquired in 2013 by HiSilicon, the chip division of Huawei. Huawei is the global No.2 telecom solution provider and uses approximately one sixth of all photonics components produced in the world.

Huawei aims to significantly reduce the cost of these components by investing aggressively in silicon photonics research and development and implementing solutions based on this technology. Huawei Technologies R&D Belgium, or Belgian Research Centre (BeRC), will be at the heart of this research and development.

Huawei’s Belgian Research Centre (BeRC) is a fast growing research institute in the Centre of Europe. BeRC’s vision is to be a world-leading research center for innovative technologies and platforms enabling the development of world-class products and solutions. BeRC’s mission is to strengthen our competence in Huawei’s core technologies, adding value to platforms, products and solutions, creating and promoting thought leadership by making innovation a reality and valuable.

Huawei Technologies R&D Belgium is now looking for a Director of R&D, Silicon Photonics Group with a strong expertise in both Photonics Integrated Circuit (PIC) design using silicon, silica or InP, a good background in process integration and exposure to the opportunities for photonics integrated circuits in telecom/datacom as well as non-telecom domains. He/she will already have had responsibility of bringing products to market amid tight deadlines and exacting specifications. He/she will lead all design and process development activities, organizing and personally contributing to the innovation of new products and designs.

Within the scope of your areas of expertise, your responsibilities include the following:

Design

Ensure the design projects are executed on time, within budget and meet specifications
Regularly review, offer guidance and technical insight to the design team

Process Platform

Translate product requirements into specifications for chip design and process platform, evaluating available trade-offs
Work with the Process Development Team Leader to define required process modifications or optimisations to realize required photonics structures. Plan, budget, win approval and execute the associated developments.

Winning new projects

Finding new business opportunities and getting a buy-in from important stake-holders
Ensuring a detailed understanding of the application, potential photonics solutions and evaluating the pros/cons of each, Performing business analysis and technical risk evaluation of proposed designs/solutions.
Active involvement in networking, establishing relevant contacts in academia and industry, writing proposals for collaboration projects.

Management and Leadership

Mentor, coach and appraise team leaders, help build their team through successful recruitment and high retainment levels
Represent the Belgian team within Huawei
Cooperate with other related R&D groups in Europe

Requirements & Qualifications:

Strong management experience with the ability to provide others with clear direction and leadership e.g. lead a project team to cooperate with a team of international experts in different areas including marketing, R&D and standardization.
Minimum 10 years’ experience in photonics of which five years in the development of Photonics Integrated Circuits. Proven track record of delivering designs which end up in production.
A detailed understanding of process integration relevant to Photonics Integrated Circuits (either III-V or Silicon photonics)
Ability to quickly understand new application areas and product requirements
Experience as interface between industry, academia, authorities and institutions in Europe
Excellent communication and presentation skills
Critical and analytical style
Master or PhD in related technical discipline
Experience with Chinese business culture is an advantage
Fluent in English (written and spoken)
Dutch or Chinese language knowledge is a plus

If you desire to embrace the above described challenge, with a very high level of technical innovation, being part of a multicultural team and growing environment, feel free to contact us. Driving future technologies with focus on customer satisfaction is one of our missions. Join us!

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Energy-efficient training algorithms Student Internship

Leuven, Belgium

Internship

Partial Remote Job

Huawei Leuven Research Center

Our newly founded Fundamental Theory Lab part of Belgium Research Center (Leuven, Belgium) will play a leading role in researching new computational technologies for next generation networks. Research activities range from mathematical and computational optimization up to their application to sequential decision processes, online optimization for scheduling, predictive network modeling, automated pattern detection/extraction, automated data labeling and as well as fast converging solvers.

Description: this internship is situated in the domain of computational methods for neural networks; the training of neural networks by backpropagation does (often) not account for energy consumption considerations and the resulting constraints on the properties and usage of the learned model. However, these constraints are of fundamental importance in enabling autonomy of devices executing the learned model(s).

Goal: the main goal of this internship is to formulate, design and evaluate optimization methods and algorithms that minimize the neural network loss/error function (associated to simple regression/ classification tasks) under energy constraints.

Tasks: the tasks assigned to the intern -under the supervision of a Post-Doc level promotor- include but are not limited to:

Development and evaluation of energy consumption models
Design and numerically evaluation of first order iterative optimization algorithms for solving of nonlinearly constrained problems for the training of multi-layer neural networks
Comparison against non-constrained training algorithms (accuracy vs. complexity vs. energy consumption)

Duration:

Short duration (from 3 to 6 months): suited for MSc curriculum course or other voluntary activity conducted in academic context.
Long duration (up to 12 months): suited for MSc thesis internship
Note well: following Belgian Law, being a student internship (no working contract) only direct costs may be reimbursed.

Candidate profile and Position requirements:

At least : last year of MSc degree in Applied mathematics, Mathematical engineering, Numerical Mathematics but also Theoretical computer science, Computer science engineering.
- Note well: candidate must be enrolled or already obtained their University degree from an academic institution of one of the EU country.
Experience in either
- Continuous optimization and nonlinear programming together with good knowledge of iterative methods for the solving of constrained nonconvex optimization problems
- Stochastic optimization and related methods including stochastic approximation, sample average approximation, stochastic splitting methods etc.
Experience in energy-/power consumption models for computing systems is considered as a plus.
Good knowledge of programming language (C/C++, FORTRAN), functional programming language (LISP, Julia, etc.) or numerical programming languages (such as Octave) is considered as a plus.
Excellent Communication skills - Presentation, oral and writing skills.

Application requirements

Certified copy of the MSc diploma/certificate shall be included in annex of the CV.
- The CV shall indicate the detailed coordinates of the current or eventually the last academic institution and department of the candidate.
- The CV shall include a detailed list of publications/achievements in relation to the job description.
Note well: the candidate must follow or have obtained his/her MSc degree from an academic institution of one of the EU countries.

Starting date:

1st 2022 (earliest) – Sep.1st 2022 (latest)

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HRBP

Amsterdam-Zuidoost, Netherlands

Employee

No remote work

Huawei Amsterdam Research Center

HRBP for R&D team in the Netherlands

Job responsibility

Hire technical experts and engineers for the Netherlands R&D team. Work including: sourcing, HR interviews, offer design and negotiation, and complete Huawei's internal recruitment process.
Undertake the tasks of the R&D HR team in the Benelux region and support the achievement of the work objectives of the Benelux R&D HR team
Establish contacts with renowned universities from the Netherland and attract local outstanding fresh graduates who are willing to join Huawei after graduation.
On a regular basis, assist business executives to complete employees' performance evaluation, personnel and post matching, bonus distribution, etc.
As a HRBP, serve as an effective communication channel between employees and the company, assist in solving problems and difficulties encountered in team management.
Ensure the external legal compliance and internal regulation of HR R&D team.

Work experience and competence required:

Understand the Netherland’s labor law. Having more than 3-year work experience in HR field in the Netherland for more
Strong learning abilities, quick understanding and assimilation of Huawei HR management regulation and operation system.
Excellent communication skills and team work abilities.
Fluent in Dutch and English

Work report to: Direct supervisor: Director of Amsterdam Research Center

Working place: Huawei Technologies, 1101 CN Amsterdam- Zuidoost, NL

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Internship in Accelerated Training with Fast Converging Solvers

Leuven, Belgium

Student

Huawei Leuven Research Center

In neural-based learning, a generalized model must be extracted and selected from a finite set of input-output samples drawn from an unknown probability distribution that should be descriptive enough for unseen/new input data. Due to the nonconvexity of the set of functions that can be approximated by neural networks and the nonconvex property of the objective function to be minimized, training performs by solving nonconvex optimization problems over nonconvex sets. These neural networks are primarily those involved in nonlinear function approximation underlying automated pattern detection/ extraction and recognition/identification such as multi-dimensional interaction modeling and their synthetic representation. In the context of communication networks, for instance, trained neural models aim at augmenting -or even replacing- current local routing and forwarding processes. Due to various operational or performance requirements, the corresponding tasks require in turn the solving of constrained nonconvex optimization problems.

On the other hand, despite recent advances in automatic differentiation (AD) algorithms and software, incorporating automatic differentiation tools in optimization solvers remains largely unexploited. Commonly, the solving of bound-constrained nonlinear optimization problems with, e.g., the Newton method or the Augmented Lagrangian Method (ALM), require the evaluation of the objective function, its gradient and the (sparsity pattern of the) Hessian matrix. Additionally, constrained optimization problems also involve providing the sparsity pattern and the Jacobian matrix of the constraints. The time and resource required to obtain this information and verify their correctness can be relatively large even for simple problems. Nowadays, optimization problem-solving environments provide modeling language and state-of-the-art optimization solvers together with packages that are capable to compute first-order information, e.g., derivatives, gradients. However, AD remains largely unexploited for generating these quantities; requiring consequently to run the entire framework and its packages altogether to solve nonlinear optimization problems. Moreover, for constrained neural networks training, it would be beneficial to solve the corresponding optimization problems by means of unified AD tools. In this context, the main goal is to blend AD tools that automatically generate the required first- and second-order quantities together with nonlinear optimization methods such as ALM for constrained problems.

Objective: instigate and investigate automatic differentiation tools for nonconvex optimization solvers that can rapidly converge with few function and derivative evaluations as well as provide and improve second-order information with the same efficiency and reliability as available for first-order information.

Task(s): design/formulate, develop and numerically evaluate enhancements of existing computational methods/algorithms such as ALM for solving constrained nonconvex optimization problems. To address the computational performance objectives, the candidate will also actively participate to the design (extension) and evaluation of (existing) automatic differentiation tools for solving such optimization problems. These tasks will be realized under the supervision of a senior (postdoc-level) researcher.

Duration: from 3 months to 1 year (max.)

Candidate profile:

If MSc thesis: the candidate must be following the last year of the curriculum in, e.g., Applied mathematics, Math. engineering, Theoretical computer science, Computer science engineering. Detailed coordinates of MSc promotor and his/her academic affiliation must be provided in the CV application form.
If internship: the candidate must have completed his/her MSc (in one of these disciplines) and ideally realized a thesis in one of the following domain(s): nonlinear programming, computational methods and algorithms for nonconvex optimization (incl. second order iterative methods, subspace methods, etc.), automatic differentiation. Copy of the MSc diploma/ certificate shall be included in annex of the CV. The internship can also be considered as part of post-MSc graduation or PhD graduation program.
Good knowledge of functional programming language (LISP, Julia, etc.) is considered as a plus.

Note well: candidate must have obtained their University degree from an academic institution of one of the EU country.

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Internship in Constrained Nonlinear Optimization

Leuven, Belgium

Student

Option for/Allows Remote Job

Huawei Leuven Research Center

In the context of context of communication networks, neural networks are primarily involved in automated pattern detection/extraction and recognition/identification tasks in online signal processing (packet flows for instance) but also sub-graph analysis (network topology and path properties). Neural models aim at augmenting -or even replacing- current local routing and forwarding models and processes. For this purpose, a generalized model must be extracted and selected from a finite set of input-output samples drawn from an unknown probability distribution that should be descriptive enough for unseen/new input data. However, due to the nonconvexity of the set of functions that can be approximated by neural networks and the nonconvex property of the objective function to be minimized, their training performs by solving nonconvex optimization problems over nonconvex sets. Moreover, due to various operational or performance requirements, training further involves the solving of constrained nonconvex optimization problems.

On the other hand, automatic differentiation (AD) onto which neural training algorithms relies, remains largely unexploited in optimization solvers. Commonly, the solving of bound-constrained nonlinear optimization problems with, e.g., the Newton method or the Augmented Lagrangian Method (ALM), require the evaluation of the objective function, its gradient and the (sparsity pattern of the) Hessian matrix. Additionally, constrained optimization problems also involve providing the sparsity pattern and the Jacobian matrix of the constraints. The time and resource required to obtain this information and verify their correctness can be relatively large even for simple problems. Nowadays, optimization problem-solving environments provide modeling language and state-of-the-art optimization solvers together with packages that are capable to compute first-order information, e.g., derivatives, gradients. However, AD remains largely unexploited for generating these quantities, requiring in turn to run the entire framework and its packages altogether to solve nonlinear optimization problems. For energy-constrained neural networks training, it would also be beneficial to solve the corresponding nonconvex optimization problem (including nonlinear inequality constraints) by means of unified AD tools. Indeed, combining AD tools that automatically generate the required first- and second-order quantities together with nonlinear optimization methods such as ALM yields a promising method.

Objective: investigate and design nonlinear programming methods for solving constrained nonconvex optimization problems that can rapidly converge with few function and derivative evaluations. Ideally the proposed algorithm would also improve second-order information with the same efficiency and reliability as available for first-order information.

Task(s):

Formulate, develop and numerically evaluate enhancements/extensions of computational methods/algorithms including ALM for solving nonlinearly constrained nonconvex optimization problems.
To address the computational performance objectives, the candidate will also actively participate to the design (extension) and evaluation of (existing) automatic differentiation tools for solving such optimization problems.
Integration of these tools into a unified AD framework will be realized in cooperation with computational/numerical method experts. These tasks will be realized under the supervision of a senior (postdoc-level) researcher.

Duration:

Short duration (from 3 to 6 months): suited for MSc curriculum course
Long duration (up to 12 months): suited for MSc thesis internship
Note well: unpaid student internship (no working contract), only direct costs are reimbursed up to 660 Euros per month

Candidate profile:

MSc (or last year of MSc curriculum) in applied mathematics, mathematical engineering, theoretical computer science, or computer science engineering.
Strong nonlinear modeling and mathematical programming skills.
Very good knowledge of techniques such as first-/second-order iterative methods (PGD/PPD, ALM, ADM(M), etc.), inexact methods and/or Krylov subspace methods ((B)CG, Lanczos, GMRES, MINRES, Arnoldi, etc.) for nonconvex optimization problems.
Experience in programming with nonlinear optimization libraries, e.g., LANCELOT/ CUTE, MINOS, TRON, NLopt, etc.
Excellent written, verbal and interpersonal communication skills.
Knowledge of functional programming language (LISP, Julia, etc.) is considered as a plus.

Application requirements

Certified copy of the MSc diploma/certificate shall be included in annex of the CV.
The CV shall indicate the detailed coordinates of the current or eventually the last academic institution and department of the candidate.
The CV shall include a detailed list of publications/achievements in relation to the job description.
Note well: the candidate must follow or have obtained his/her MSc degree from an academic institution of one of the EU countries.

Starting date: May.1st, 2022 (earliest) – Oct.1st, 2022 (latest).

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Internship in Nonlinear Inverse Problems

Leuven, Belgium

Student

Huawei Leuven Research Center

Inverse problems seek to reconstruct the unknown model parameters characterizing the system under investigation from measured data. More precisely, nonlinear inverse problems start by considering a nonlinear operator between the parameters, and acquired information / observation about them, i.e., data or measurements. This operator constructs a model for the available data, assumed to depend only on these parameters. Since the inverse problem is the inverse of the forward problem, this operator is often referred to as the forward operator. n nonlinear inverse problems, the forward operator being nonlinear, the model parameters depend in a nonlinear way of the state of the system and therefore on the observations available on it.

However, inverse problems are typically ill-posed, as opposed to the well-posed problems (verifying existence, uniqueness, and stability of the solution(s)). Also inverse problems are also typically ill-conditioned, i.e., a small change in the input induce a large change in the response. Hence, to tackles them, nonlinear regularization functionals are often introduced in the objective function to prevent overfitting. The specific context of this internship sits when the resulting minimization problem also involves inequality constraints on the model parameters or some functions of them. These constraints are important to avoid invalid or non-significant values for the model parameters.

Task: Design and compare different numerical solving algorithms associated to different constrained nonlinear optimization methods. Evaluate and compare these algorithms both formally and numerically using various (synthetic or real) benchmark cases including network tomography, network properties inference, etc. These tasks will be realized under supervision of senior (postdoc-level) researcher.

Duration: from 6 months to 1 year (max.)

Candidate profile:

if MSc thesis: the candidate must be following the last year of the curriculum in, e.g., Applied/ Numerical mathematics, Math/Mechanical engineering, Theoretical computer science, Computer science engineering. Detailed coordinates of MSc promotor and his/her academic affiliation must be provided in the CV application form.
if internship: the candidate must have completed his MSc (in one of these disciplines). Copy of the MSc diploma/certificate shall be included in annex of the CV. The internship can also be considered as part of post-MSc graduation or PhD graduation program.
Good knowledge of networked systems is considered as a plus.

Note well: candidate must have obtained their University degree from an academic institution of one of the EU country.

Starting date: Jun.1st, 2022.

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Junior Business Development Manager

Leuven, Belgium

Employee

Partial Remote Job

Huawei Leuven Research Center

Function: Business Development Manager
Department: Hisilicon Strategy & Business Development Department
Location: Belgium (Huawei Belgium Research Center - BeRC)
Experience: junior
Reporting to: Sr. Director Strategy & Business Development

The role spans activities in Europe/EMEA region: identifying new business development opportunities
and sourcing of potential M&A or investment targets.
Specific focus is on semiconductor related technology companies and startups.
The candidate should be able to easily communicate and network externally and effectively report and
communicate to headquarters.

Work requirements:
The candidate will be responsible for the following activities:
* build relationships with European companies, startups, knowledge and incubation centers and VCs
* organize business/technical evaluations and due diligence together with expert colleagues and HQ
* organize and accompany business trips together with experts from HQ
* tracking and reporting of progress and presenting summaries in key domains to HQ

Qualifications/Experience:
* background in engineering and/or economics (minimum Master degree)
* experience in business development is a plus
* open to multi-cultural environment

* English, French &/or Dutch are a must, Chinese is a plus

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Junior Network Optimization Research Engineer (MSc)

Leuven, Belgium

Employee

Huawei Leuven Research Center

Junior Research Engineer in Network Optimization (MSc)
Junior Research Engineer with MSc thesis completed (up to 2 years of
experience after completing MSc degree) in Computer science, Computer
science engineering, Math. engineering, Operational research

Goals
Together with the research & engineering team in advanced computational optimization focused on network applications, you will contribute to the following
 Develop methods and algorithms customized for network optimization problems involving nonlinear coupling constraints, nonconvex/nonlinear composite objective functions, etc.
 Evaluate numerically/experimentally these network optimization algorithms on selected use cases with real-life data sets.
 Integrate them as part of product-grade solver framework for automated execution

Skills and competences
 Network optimization including network design, routing/traffic assignment, resource allocation, flow/resource scheduling, etc.
 Optimization methods/algorithms (must) : mixed integer nonlinear programming (must) and at least one of the following :

o Iterative methods: first order methods (linesearch methods, subspace methods, etc.), Gauss-Siedel, Jacobi, Newton-Raphson methods, etc., Primal-dual methods (Lagrangian methods, etc.), interior point methods
o Projective/proximal methods
o Stochastic methods

 Programming (must) : strong skills in C/C++, Fortran, and Octave
 Solving frameworks : (MI)NLP (e.g. Gurobi, SCIP, Couenne/COIN-OR, SHOT/COIN-OR, Algencan, Bonmin, etc.), Subsolvers (e.g. MIP: CPlex, NLP: Ipopt, Conopt)

CV
Provide complete CV with both research and work/practical experience, including elements that demonstrate
 Outstanding programming skills (experimental code or ICPC winner) in C/C++ and Fortran –note: excellent skills in Octave programming is considered as a plus
 Expertise in network optimization methods and algorithms: list of achievements and publications (Springer: JOTA, COAP, AMO, JGO, NUMA, etc. Wiley : Networks, IEEE JSAC, IEEE Transactions on Communications, etc.) –note: theoretical knowledge of abstract algorithms not sufficient
 Excellent English level proficiency (both oral and written)

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Junior Network Optimization Research Engineer (PhD)

Leuven, Belgium

Employee

Huawei Leuven Research Center

Huawei Gent Research Center

Junior Research Engineer in Network Optimization

Junior Research Engineer with PhD thesis completed (up to 2 years of experience after completing PhD degree) in Computer science, Computer science engineering, Math. engineering, Operational research

Goals

Together with the research & engineering team in advanced computational optimization focused on network applications, you will

Develop methods and algorithms customized for network optimization problems involving nonlinear coupling constraints, nonconvex/nonlinear composite objective functions, etc.
Evaluate numerically/experimentally these network optimization algorithms on selected use cases with real-life data sets
Integrate them as part of product-grade solver framework for automated execution

Skills and competences

Network optimization including network design, routing/traffic assignment, resource allocation, flow/resource scheduling, etc.
Optimization methods/algorithms (must) : mixed integer nonlinear programming (must) and at least one of the following :
- Iterative methods: first order methods (linesearch methods, subspace methods, etc.), Gauss-Siedel, Jacobi, Newton-Raphson methods, etc., Primal-dual methods (Lagrangian methods, etc.), interior point methods
- Projective/proximal methods
- Variational methods
Programming (must) : strong skills in C/C++, Fortran, and Octave
Solving frameworks : (MI)NLP (e.g. Gurobi, SCIP, Couenne/COIN-OR, SHOT/COIN-OR, Algencan, Bonmin, etc.), Subsolvers (e.g. MIP: CPlex, NLP: Ipopt, Conopt)

CV

Provide complete CV with both research and work/practical experience, including elements that demonstrate

Outstanding programming skills (experimental code or ICPC winner) in C/C++ and Fortran –note: excellent skills in Octave programming is considered as a plus
Expertise in network optimization methods and algorithms: list of achievements and publications (Springer: JOTA, COAP, AMO, JGO, NUMA, etc. Wiley: Networks, IEEE JSAC, IEEE Transactions on Communications, etc.) –note: theoretical knowledge of abstract algorithms not sufficient
Excellent English level proficiency (both oral and written)

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Logic Devices R&D Engineer

Leuven, Belgium

Employee

Huawei Leuven Research Center

We are looking for highly motivated, team players to support engineering activities at our Huawei Belgium Research Center, Leuven.

To reach our goal we are looking R&D Engineer for Logic Devices

Report to the Advanced Technology Team based in Leuven, engaging in defining roadmap through extensive device data analysis, metrology and TCAD (Technology Computer Aided Design) work.

Our team’s mission includes but is not limited to:

Path-finding work to define future logic technology nodes and scaling
New technology evaluation
Next generation device/interconnection targeting and enablement
Co-work & drive our research partners globally (internal and external)
Analyzing semiconductor technology trends, define technology roadmap

Assignment Description: We are offering a long term R&D Engineer position enabling you to join the leading edge of semiconductor technology R&D.

The successful candidate will be working in close collaboration with the process technology and design teams spanning from the advanced semiconductor manufacturing, to the IC architecture and physical design. He/she will be expected to contribute to the definition of key technology parameters enabling robust and competitive design of our flagship mobile and network chips for better performance, lower power, and lower area at lower cost, giving the best and realizable PPAC outcome. This role requires the adoption of DTCO methodologies all the way from the identification of manufacturing capabilities to the build-up of process assumptions, selection of design rules together with their trade-offs. The role further requires critical thinking with emphasis on process module risk evaluation and providing innovating, breakthrough solutions; day-to-day communication with cross-disciplinary teams (internal & external), and our foundry / EDA / research partners on-site and across the globe. Strong communication skills, ability to work independently and to organize are essential.

The role offers competitive salary package matching global standards plus provides working environment in world leading research center with a team of multi-national engineers and researchers, allowing possibilities for individual growth in all sectors.

Required Education and Experience:

M.Sc. or Ph.D./Post-doc in Electrical Engineering or related discipline (fresh ~ 5 years’ experience)
Strong semiconductor device understanding
Familiar with the advanced semiconductor process and devices (e.g. finFET, GAA)
Understanding of unit process modules and technology
Excellent analytical skills with a detailed mindset
Good communication skills and strong team-player
Able to work independently
Willing to relocate to Leuven (Belgium) region

Location: Leuven (BE), 100 % on site

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Machine Learning (Data) Scientist - Language Understanding

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

We are looking for a Machine Learning Applied Scientist to join our Search Engine team in Amsterdam

The Search Team in Huawei’s Amsterdam R&D Center is building an industry-leading Cloud Search product that powers the search experience on Huawei mobile phones. The team is responsible for advanced components of the search engine, including question answering, offline document analysis and machine translation. We are looking for a Machine Learning Applied Scientist to join our team and together build the future of search.

Our mission is to build a state-of-the-art search experience using the latest techniques in information retrieval, machine learning and natural language processing. We maintain active collaboration with local universities to push the envelope on search and deliver the best customer experience.

Responsibilities

You will work within a fast-paced team of applied scientists and engineers. You will contribute to all stages of the machine learning lifecycle and help maintain a positive team culture. Your responsibilities will include:

Create and implement new algorithms using the latest, bleeding-edge, advancements in ML research to solve applied problems in language understanding, such as question answering, sentiment analysis and information extraction.
Research new directions to solve problems in language understanding, such as novel architectures, quality estimation, model robustness and techniques for low-resource languages and domains
Work together with other applied scientists and machine learning engineers in an agile team

Required Qualifications:

Degree in Computer Science, Physics, Mathematics or related field
Broad knowledge of fundamentals and state-of-the-art in machine learning and statistics focusing on Natural Language Processing and/or Information Extraction
Excellent coding abilities in Python (other languages like Java and Go is a pro)
Experience with at least one deep learning framework like PyTorch or Tensorflow.
Working experience with SQL, ElasticSearch, and big data technologies
Excellent communication and collaboration skills

Preferred Qualifications:

Research contributions in one of the top tier NLP conferences (i.e. EMNLP, ACL, NAACL, etc.)
Experience processing non-European languages

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Machine Translation Scientist

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

Machine Translation Scientist

Huawei R&D Center Amsterdam is looking for a Machine Translation Scientist to join our growing machine translation team and work on large scale neural machine translation systems. We build and maintain cutting-edge machine translation systems for a variety of challenging language pairs that find application in Huawei’s Cloud Search environment. The team actively researches new directions in machine translation to improve our models and open new avenues for application. We are looking to expand our team to cover more language pairs and more domains. This is a great opportunity for an expert in machine translation who is looking to have real world impact at a large scale.

Responsibilities

You will work with a team of applied scientists and engineers who are responsible for all stages of the machine translation model development, including data set selection and filtering, model training and evaluation and domain adaptation. Your responsibilities will include:

Design, develop, test, maintain and debug software programs for the key stages of the machine translation model lifecycle ;
Create and implement new algorithms to solve applied problems in machine translation, such as cross-lingual transfer, domain-adaptation, model compression or data set filtering ;
Research new directions to solve problems in machine translation, such as multilingual translation, quality estimation, model robustness and techniques for low-resource languages and domains;
Publications are possible.

Primary Location

Amsterdam

Required Qualifications:

PhD in natural language processing related field or equivalent research experience;
Experience in building machine translation systems;
Excellent coding abilities in Python and mastery of at least one deep learning framework;
Strong familiarity with machine translation frameworks.

Preferred Qualifications:

Research contributions in the field of machine translations in one of the top tier NLP conferences (i.e. EMNLP, ACL, NAACL, etc.);
Proven record of contributions to open source machine translations or sequence to sequence modelling toolkits (or codebases);
Intensive experience in one of the machine translations research area.

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Predictive Network Modeling Research Internship

Leuven, Belgium

Student

Huawei Leuven Research Center

Rough network data being typically unlabeled limits application of neural networks to unsupervised learning tasks (learning from unlabeled data). Tools for automated network data labeling becomes thus a first-level priority to enable supervised learning tasks (learning from hypothesis/candidate models) by means of neural networks. These neural networks are primarily those involved in nonlinear function approximation underlying automated pattern detection/extraction and recognition/identification such as multi-dimensional interaction modeling and their synthetic representation. In the context of communication networks, for instance, labeled datasets can be used for training neural models to augment -or even replace- current local routing and forwarding process.

On the other hand, a label can be considered as encoding the value of the objective function underlying the machine learning task or the parameter of a model (structured learning). Hence, automated labeling implies that either this objective or the model are formally known. This operation can be realized either in batch or online mode. The former typically assumes that the main performance criteria relates to the size of the input (assumed to be complete) that needs to be processed to reach a given accuracy level. The latter implies time-constrained processing of incoming input following different arrival processes; thus, the number of cycles/inter-arrival times required to reach a given accuracy level.

Objective: automatic labeling method of network data, including spatio-temporal data (traffic, etc.), structural data (topological, etc.)

Task: blends modeling, algorithmic and experimental research; the candidate will have the opportunity to explore, evaluate and compare different labeling algorithms by formal and numerical methods. These tasks will be realized under supervision of senior (postdoc-level) researcher.

Duration: from 6 months to 1 year (max.)

Candidate profile:

if MSc thesis: the candidate must be following the last year of the curriculum in, e.g., Applied mathematics, Math engineering, Theoretical computer science, Computer science engineering. Detailed coordinates of MSc promotor and his/her academic affiliation must be provided in the CV application form.
if internship: the candidate must have completed his MSc (in one of these disciplines). Copy of the MSc diploma/certificate shall be included in annex of the CV. The internship can also be considered as part of post-MSc graduation or PhD graduation program.
Good knowledge of traffic/network simulation is considered as a plus.

Note well: candidate must have obtained their University degree from an academic institution of one of the EU country.

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RF IC Contest 2022 : Architectures and circuit design for Analog, RF, mmWave

Leuven, Belgium

Other

Huawei Leuven Research Center

Topic: Architectures and circuit design for Analog, RF, mmWave integrated circuit design for low power applications, IoT and wideband communication system

Contest Rules

CANDIDATES

The contest is open for PhD students, recently (<2y) graduated Ph.D.’s and Post-docs affiliated to universities and R&D institutes in the Benelux.

SCHEDULE

15 Sep 2022 - 31 Oct 2022: Submission period

20 Nov 2022: Decision on the shortlist of finalists. Invitation sent out to shortlisted candidates on the deadline to submit onsite presentation papers.

15 Dec 2022: Hybrid (onsite or virtual) presentation by the finalists on the submitted papers, followed by award ceremony.

SUBMISSIONS

General

The subject of the paper should focus on State-of-the-Art IC design topics in the following domains (not limiting):

Analog
RF and mmWave integrated circuit design for low power applications
IoT
Wideband communication systems
etc

The submissions should consist of a recently published conference or journal paper or a research reports summary (8 pages maximum). Joint-participation of equally valued contributors is allowed. In such case potential award would be granted to the team. Every participant can only submit 1 publication. Co-authorship of a different submission is allowed. Also, please note that previously submitted paper cannot be resubmitted.

All submissions should be complete, written in English and submitted via the application button below, respecting the given schedule.

The following personal details of the candidate should be included:

-Name and surname;

-Phone number and/or email address of the candidate;

-Education level of the candidate;

The submitted content should be original and should not violate, plagiarize, or infringe the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

Huawei reserves the right to cancel the event due to unforeseen reasons in which case we will do everything we reasonably can to let you know.

PowerPoint presentation

The selected shortlist consisting of the 10 finalists will be required to give a PowerPoint presentation on their submitted work at the on-site award ceremony in view of the selection of the winner and the final ranking, as set out below. This PowerPoint presentation should be limited to a duration of 20 minutes.

SELECTION
1. General : The evaluation will be done by Huawei experts across Europe.
2. Published papers / Research reports

To select the shortlist of candidates, consisting of 10 finalists, the Huawei experts will evaluate the submissions on the basis of the following criteria:

-Quality and thoroughness of the research;

-Innovation and creativity of the solutions and ideas presented;

-Feasibility and commercial potential of the solutions, ideas; and

-Overall quality, clarity and conciseness of the submissions.

Presentation

The selected shortlist, consisting of the 10 finalists, will be required to give a PowerPoint presentation about their submitted work at the online award ceremony. Huawei experts will evaluate these oral presentations and the written submission and select the winners. In addition to the criteria listed in section b, following criteria will also be taken into account for the final ranking:

-Structure and content of the presentation;

-Clarity of the presentation;

-Originality and creativity;

-Overall quality of the presentation.

AWARD : All finalists will receive attractive prizes

Intellectual property rights and warranties

When making a submission, each candidate warrants to be the original author of that submission. For the avoidance of doubt it is explicitly understood that the mere participation in this contest will not result in any transfer of intellectual property rights.

When making a submission, each candidate furthermore warrants not to violate, plagiarize, or infringe the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

Finally and for the avoidance of doubt it is explicitly understood that candidates should not disclose any confidential information pertaining to their research and/or submissions.

DATA PRIVACY

Huawei Technologies Research & Development Belgium NV and its affiliates around the world clearly understand how important privacy is for you and respect your privacy. Please carefully read the Privacy Statement before submitting your personal data to Huawei : http://www.cvwarehouse.com/downloads/CompanyDocuments/11091_HuaweiBenelux/200625_Privacy_statement_Contests_and_Events_final.pdf

EXCLUSION

Huawei will have the right to immediately exclude any candidate from the contest at any given time and/or claim the return or refund of awards that would already have been granted, if Huawei shows to have valid reasons to believe the concerned candidate engaged in unlawful behavior in connection with the contest, including but not limited to the violation, plagiarism, or infringement of the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

ORGANIZER OF THE CONTEST

The contest is organized by the following Huawei company (“Huawei”):

Huawei Technologies Research & Development Belgium NV

Technologiepark 122

9052 Zwijnaarde (Ghent)

CBE n°: 0827.031.106

LER Ghent

CONTACT email address in case of technical submission issues or questions:leuvenhr@huawei.com

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Senior Analog Power IC Design Engineer

Leuven, Belgium

Employee

Partial Remote Job

Huawei Leuven Research Center

About the job

We are seeking principle Power Management IC designers to join our team. Candidates will be asked to design innovative, high performance integrated circuits which include DC-DCs, AC-DCs, Gate-Drivers, and multi-functional power management circuits.

Job Responsibilities

Translate system requirements to chip and block level architecture and specifications
Circuit design of high performance PMIC blocks (DC-DC, AC-DC, Gate Driver, etc.), responsible for system-level and block-level design and verification
Work with and provide guidance to layout engineers and monitor the progress of the layout
Collaborate with validation, product engineering and test engineering teams to enable successful transfer to production

Job Requirements

Master degree in Microelectronics/Electrical engineering
Extensive experience in smart gate drivers (low-side/high-side/isolated driver) design
Extensive experience in switching regulators design (multi-phase buck, boost buck-boost, fly-back, PFC, LLC) converters
Good understanding of different power architectures and control methods
Expertise in EDA tools (Spectre, Simplis, Matlab)
Deep understanding of power stage design and layout design
Knowledge of bipolar, BiCMOS, and BCD process technologies
Strong analytical and problem-solving skills
Strong inter-personal, teamwork and communication skills are required

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Senior DWS Service R&D engineer

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

After 11 years of development, HUAWEI CLOUD GaussDB (DWS) is an industry-leading enterprise-level cloud distributed data warehouse service. Provides data analysis services for 1700+ customers worldwide. Benchmarking with external products such as Teradata, Oracle, and HANA Huawei provides O&M-free, online expansion, and efficient multi-source data loading capabilities. It is compatible with the PostgreSQL ecosystem and provides cost-effective online analysis services for massive enterprise data.
Welcome to join the HUAWEI CLOUD EI Service Product development and research. You will work with top experts in the big data analysis domain at home and abroad.

Job Responsibilities:
1. Deep insights into cutting-edge technologies and products in the data analysis domain from both the industrial and academia, participates in R&D project planning in the direction of technology leadership and product experience improvement.
2. Undertake the research of architecture innovation and key technologies development, build up future-oriented and industry-leading product with core competitiveness.
3. Cooperate with top researchers in the industrial and academia , participates in research on cutting-edge issues in the database domain.

Job requirements:
1. Proficient in C, C++, Java, Python, etc.
2. Have a good R&D background and professional knowledge in databases, big data systems, distributed systems, and high-performance computing. Have research background or product development experience in core modules (such as optimizers, executors, and storage systems).
3. Have experiences in the development and maintenance of cloud service and DevOps.
4. Clear working ideas, good communication skills and technical learning skills, good coding habits, strong self-study ability and self-improvement desire;

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Senior LakeHouse Service R&D engineer

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

HUAWEI CLOUD MRS is the fastest growing star service of HUAWEI CLOUD. The MRS-based LakeHouse solution is fully compatible with open-source big data analysis technology stacks such as Spark, Flink, Hive, and Presto. In addition, it provides a self-developed high-performance online analysis engine. Based on the leading storage-computing separation architecture, converged metadata, and converged table engine, Huawei provides high-performance and high-availability converged analysis capabilities for one-stop stream processing, batch processing, and interactive query.
Welcome to join the HUAWEI CLOUD EI Service Product development and research. You will work with top experts in the big data analysis domain at home and abroad.

Job Responsibilities:
1. Undertake the pre-research and software development of key technologies for LakeHouse service products, and develop future-oriented and industry-leading data analysis technologies.
2. Build up cloud services with leading technologies and excellent experience through industry comparison analysis, listening to customer's feedback, and problem analysis.
3. Participate in technical competitions of key customer projects of LakeHouse product , tackle challenges and problems, support the success of data analysis customer projects.

Job requirements:
1. Proficient in C, C++, Java, and Python.
2. Have a good knowledge of data platforms, such as data warehouse, big data, and data lake warehouse.
1.1 Be familiar with the SQL optimizer and executor of the data system. Experienced in Cost-Based Optimizer and Adaptive Query Execution is preferred.
1.2. Experienced in open source big data, familiar with open source big data technologies, such as Spark/Trino/Presto/Flink/ClickHouse, is preferred.
1.3. Vectorization/Query Compilation experiences is preferred, for example, familiar with SIMD programming, CodeGen/LLVM, Arrow vectorization processing, etc.
1.4. Experienced in LakeHouse transactional data systems is preferred, e.g. familiar with Delta Lake, Iceberg, Hudi;
3. Have experiences in the development or maintenance of cloud computing, high-performance computing, or distributed systems, experiences in cloud service development, DevOps practice, and code contributors/committers to big data open source community projects are preferred.
4. Clear working ideas, good communication skills and technical learning skills, good coding habits, strong self-study ability and self-improvement desire;

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Senior Product Manager Searching Tools

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

Responsibilities

Build a long term product vision and value proposition based on customer needs, competitive analysis and overall Huawei CloudService strategy. Product differentiation is key.
Define product roadmap and set engineering priorities. Work closely with Huawei mobile phone and cloud service teams to collect market feedback and re-align roadmaps.
Create detailed functional and non-functional requirements and work closely with R&D to guide the product development phase on all dimensions including content, timing, quality etc.
Evangelize product vision and value propositions to customers, partners and internal stakeholders.
Responsible for GTM readiness, sales enablement and business development support.
Support business operations and monetization teams in defining and implementing an appropriate licensing and commercial model.

Qualifications

Prior experience as a Product Manager defining and managing product roadmaps, business case analysis, customer presentations etc.
A deep sense of search market, product and ecology.
Expert level knowledge either in the NLP, Knowledge Graph, Bigdata platform, Information Retrieval, etc.
Data driven approach to problem solving and pay attention to detail without losing sight of the big-picture.
Strong communication and influencing skills – both for internal and external stakeholders.
Independent thinker and self-starter that operates with a sense of urgency and is able to research and present findings with minimal direction.
A pragmatic approach and the ability to thrive under pressure of constant change and moving objectives. Ability to work in a changing, dynamic environment.
Good understanding of the software development life cycle and product life cycle.
Knowledge of data analytics, statistics, machine learning and willingness to build advanced skills in this area.
Product manager experience in search related companies like Google Search, Microsoft Bing, TomTom, Hear, Yandex, etc. is a plus.

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Silicon Photonics PhD Student Contest 2022

Gent, Belgium

Other

Huawei Gent Research Center

Contest rules:

CANDIDATES

The contest is open for PhD students and Post docs studying at universities in Europe.

SCHEDULE

01/07/2022: Start of submission period

16/09/2022: End of submission period

End October 2022: Invitation sent out by Huawei for award ceremony and announcement of the selected shortlist of candidates, with the deadline for submitting the onsite presentation paper.

01/12/2022: Onsite presentation by the finalists of the submitted papers, followed by award ceremony

SUBMISSIONS

a. General

The subject of the paper should focus on the broad topic of “silicon photonics” but not limited to:

Hybrid integration,
Electronic-photonic codesign,
lidar,
sensing,
co-packaged optics
etc.

The submissions should consist of recently published papers or research reports up to 4-6 pages.

All submissions should be complete, written in English and submitted via the application button below, respecting the given schedule.

The following personal details of the candidate should be included:

-Name and surname;

-Phone number and/or email address of the candidate;

-Education level of the candidate.

The submitted content should be original and should not violate, plagiarize, or infringe the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

Huawei reserves the right to cancel the event due to unforeseen reasons in which case we will do everything we reasonably can to let you know.

b. PowerPoint presentation

The selected shortlist consisting of the 10 finalists will be required to give a PowerPoint presentation on their submitted work at the online award ceremony in view of the selection of the final top 6 laureates, as set out below. This PowerPoint presentation should be limited to a duration of 15 minutes.

SELECTION

a. General

The evaluation will be done by Huawei experts across Europe.

b. Published papers / Research reports

To select the shortlist of candidates, consisting of 10 finalist, the Huawei experts will evaluate the submissions on the basis of the following criteria:

-Quality and thoroughness of the research;
-Innovation and creativity of the solutions and ideas presented;
-Feasibility and commercial potential of the solutions, ideas; and
-Overall quality, clarity and conciseness of the submissions.

c. Presentation

The selected shortlist, consisting of the 10 finalists, will be required to give a PowerPoint presentation about their submitted work at the online award ceremony. Huawei experts will evaluate these oral presentations and select the top 6 laureates from the shortlist on the basis of the following criteria:

-Structure and content;
-Clarity of the presentation;
-Originality and creativity;
-Overall quality of the presentation.

AWARD

1 person for Gold prize= 2000 euro worth of Huawei Products

2 people for First prize = 1500 euro worth of Huawei products

3 people for Second prize =600 euro worth of Huawei products

4 people for Finalist prize = 300 euro worth of Huawei Products

Intellectual property rights and warranties

When making a submission, each candidate warrants to be the original author of that submission and to hold all intellectual property rights pertaining to that submission. For the avoidance of doubt it is explicitly understood that the mere participation in this contest will not result in any transfer of intellectual property rights.

When making a submission, each candidate furthermore warrants not to violate, plagiarize, or infringe the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

Finally and for the avoidance of doubt it is explicitly understood that candidates will not be required to disclose any confidential information pertaining to their research and/or submissions. If a candidate would decide in its own discretion to disclose certain confidential information when making a submission, such information will only be used for the purpose of the contest, in particular for the evaluation of the submission made.

DATA PRIVACY

Huawei Technologies Research & Development Belgium NV and its affiliates around the world clearly understand how important privacy is for you and respect your privacy. Please carefully read the Privacy Statement before submitting your personal data to Huawei : http://www.cvwarehouse.com/downloads/CompanyDocuments/11091_HuaweiBenelux/200625_Privacy_statement_Contests_and_Events_final.pdf

EXCLUSION

Huawei will have the right to immediately exclude any candidate from the contest at any given time and/or claim the return or refund of awards that would already have been granted, if Huawei shows to have valid reasons to believe the concerned candidate engaged in unlawful behavior in connection with the contest, including but not limited to the violation, plagiarism, or infringement of the rights of third parties including copyright, trade mark, trade secrets, and privacy, publicity, personal or proprietary rights.

ORGANIZER OF THE CONTEST

The contest is organized by the following Huawei company (“Huawei”):

Huawei Technologies Research & Development Belgium NV

Technologiepark 122

9052 Zwijnaarde (Ghent)

CBE n°: 0827.031.106

LER Ghent

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Leuven, Belgium

Employee

Huawei Leuven Research Center

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Technical Lead Search Engine

Amsterdam-Zuidoost, Netherlands

Employee

Huawei Amsterdam Research Center

Huawei Search Team will leverage the best talent and infrastructure to build an industry-leading Cloud Search product that will allow Huawei mobile phone users to search over all their queries with best-in-industry with advanced user experiences, such as intention recognition, that would tremendously increase their experience. Our mission will be accomplished through utilizing advanced technologies to ensure knowledge data discovery and extraction, create intelligent experience, and design a robust data storing, indexing and querying architecture.

Responsibilities

You will work with a team of applied scientists and engineers who are responsible for all stages of the search engine including offline page storing/analysis/indexing, online querying/reranking/sorting. Your responsibilities will include technically lead Huawei Petal Search Amsterdam R&D branch, exploring state-of-art solutions covering NLP, ASR, Information Retrieval, Knowledge graph, video semantics, etc. Finishing planned projects like Machine translation, Segmenter, Question Answering, etc, according to global R&D roadmaps. Meanwhile, leading the research activities with local universities , helping constructing long-term competitiveness for Huawei Petal Search globally.

Qualifications

MS/BS in CS/EE, mathematical or machine learning related subjects.
Strong experiences in researching, designing, implementing and delivering commercial AI projects with models/software (Minimum: 8 years)
Proven track records of managing multiple teams.
Able to lead/cultivate team technically.
Solid knowledge and commercial projects background of Pytorch, Tensorflow, Keras, etc.
Experienced in real world large scale searching engine products, especially in multilingual multimodal information retrieval, time/cost efficiency of the algorithms, open-domain knowledge graph, etc.
Extensive working knowledge in Python、C、C++ 、Java、Go
Research and/or industrial background in machine learning, deep learning, natural language processing, knowledge graph, etc.
Willing and Ambitious to challenging world-level touch problems in AI and Search engine.
Good communication skills and English speaking, experienced working in a cross-culture and global distributed team

Qualifications considered a pre

PhD degree.
Working experience in MS Bing, Google Search, Booking or related global search engines.(Minimum: 5 years)
Leading professor in TOP academic research organizations in Information Retrieval, NLP, or Knowledge Graph.
Published influential papers in ACL、EMNLP、NAACL、COLING、ICLR or related TOP conferences.

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Video Semantic Retrieval Researcher

Amsterdam-Zuidoost, Netherlands

Freelance

Huawei Amsterdam Research Center

We are looking for a talented Video Semantic Retrieval Researcher who is excited to join our Search Engine team in Amsterdam

Do you love working on images, videos and a whole family of multimedia? Are you passionate about developing cutting-edge Machine Learning techniques? Do you have vision and talent to develop the next generation of search engine for innovative human-machine interaction? Then we have an element opportunity for you to make your dream come true!

The Search Team in Huawei’s Amsterdam R&D Center is building an industry-leading Cloud Search product that powers the search experience on the whole chain of Huawei devices. You will work within an international and fast-paced team of expert scientists and engineers, and be responsible for establishing state-of-the-art multimedia search engine to connect to the real-world in the most natural way.

Responsibilities

Design and develop computer vision related algorithms, based on deep learning/neural networks techniques.
Provide strong leadership in defining and articulating innovative and practical technical solutions that address various business needs for the video search channel of Huawei search engine (petal search)

Requirements

PhD in Computer Science/Engineering specializing in Computer Vision, Machine Learning, or similar fields.
Hands on experience in designing offline/real-time video processing/computer vision algorithms and applications, e.g., object detection, segmentation, tracking, recognition, classification, tagging, summarization, embedding, and retrieval.
Researching latest Academic papers and cutting-edge industrial approaches, working on break-through researching as well as applied algorithms.
Demonstrated projects with deep learning framework such as CNN, RNN/LSTM using Tensorflow, Pytorch etc.
Skilled in OpenCV and video/image processing open source libraries.
Skilled in C/C++ and Python.
Ability to scope and schedule deliverables independently, and be accountable for executing, performing and delivery.
Energetic, self-motivated and execution oriented individuals, passionate in building best in class products.

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